{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/26714"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/26714","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"The determinants of office tenant renewal","abstract":"This study empirically examines the historical probability of renewal for nearly three-hundred properties across forty-one Metropolitan Statistical Areas throughout the United States. It then investigates the factors that affect the office tenant renewal decision using linear and probit regression models.Through statistical analysis, several factors emerge as influential in the renewal decision, including the size of the occupied space, the level of employment in the market, as well as location. Logical building characteristics such as the age of the space and the size of the building did not appear to have as large of an impact on renewal probability. For the more than 15,000 individual leases in this study, the overall renewal probability was lower than expected. However, the regression analysis has revealed some explanation of the difference between the actual results and the industry accepted renewal probability rate of 75%.","abstract_html":"This study empirically examines the historical probability of renewal for nearly three-hundred properties across forty-one Metropolitan Statistical Areas throughout the United States. It then investigates the factors that affect the office tenant renewal decision using linear and probit regression models.Through statistical analysis, several factors emerge as influential in the renewal decision, including the size of the occupied space, the level of employment in the market, as well as location. Logical building characteristics such as the age of the space and the size of the building did not appear to have as large of an impact on renewal probability. For the more than 15,000 individual leases in this study, the overall renewal probability was lower than expected. However, the regression analysis has revealed some explanation of the difference between the actual results and the industry accepted renewal probability rate of 75%.","abstract_has_math":false,"creators":["Asser, Rebecca, 1978-"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Urban Studies and Planning.","school":null,"contributors":[],"advisors":["William Wheaton."],"committee_chairs":[],"committee_members":[],"year":2004,"date_issued":"2004","date_published":"2004","updated_at":"2026-07-22T22:21:17Z","subjects":["Urban Studies and Planning."],"languages":["en_US"],"rights":["M.I.T. theses are protected by copyright. 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It then investigates the factors that affect the office tenant renewal decision using linear and probit regression models.Through statistical analysis, several factors emerge as influential in the renewal decision, including the size of the occupied space, the level of employment in the market, as well as location. Logical building characteristics such as the age of the space and the size of the building did not appear to have as large of an impact on renewal probability. For the more than 15,000 individual leases in this study, the overall renewal probability was lower than expected. 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